Our group has recently introduced working real-time 3D-imaging technology capable of investigating the functional properties of the vascular bed without the need of contrast agents. This technology, referred to as Dynamic Near-infrared Optical Tomography (DYNOT), employs harmless near infrared light sources, is portable, suitable for prolonged monitoring, and is adaptable to a wide variety of clinical environments (including bedside and intraoperative). In this study, we plan to investigate the utility of this technology to detect, early-on, microangiopathy and neuropathy in the limbs of individuals genetically predisposed to contract diabetes, those with non-insulin-dependent diabetes (NIDDM) and those with insulin-dependent diabetes (IDDM) and overt symptoms of advanced microangiopathy. Planned studies are designed to test the hypothesis that measurable differences in the baseline time-frequency, auto regulatory and vasoreactivity responses of the microvasculature will correlate with the severity of disease as determined from analysis of time-series imaging data collected from the forearms and calfs of subjects. Imaging studies will involve performing dual wavelength (760 and 830 nm) tomographic measures at an image-framing rate of 3 Hz for up to 20 minutes per session. Validation of this hypothesis offers the potential to characterize the earliest effects of diabetes on the peripheral effector mechanism, thereby setting the stage for development of improved noninvasive monitoring and treatment protocols.